1. Field of the Invention
This invention relates to a video signal coding device and a decoding device, and more particularly, to the reduction of a transmission rate for video signals, and to the provision of high picture quality for transmitted video signals.
2. Description of the Prior Art
Various kinds of encoding methods have been proposed for reducing the amount of transmitted information when image information is transmitted. As one of these methods, predictive coding is known (termed hereinafter a "DPCM") which compresses the amount of information utilizing a correlation between sampled values. In the DPCM method, a predictive value for a sampled value to be subsequently coded is obtained from the decoded value of an already-transmitted sampled value, and a differential value (a predictive error) between the predictive value and the sampled value is quantized and transmitted. For use in the DPCM method, various kinds of methods have been proposed according to the method for producing the predictive value.
FIG. 1 is a block diagram showing the configuration of the most simple coding device using a preceding-value-predictive coding method. The preceding-value-predictive coding method is a method in which the decoded value of a sampled value to be transmitted immediately before the current sampled value is used as a predictive value, and a differential value between the current sampled value and the predictive value (the preceding value) is encoded and transmitted.
In FIG. 1, a sampled value X.sub.i input to an input terminal 10 is supplied to a subtracter 12, where a predictive value (the preceding value), which will be described later, is subtracted from the value X.sub.i. A quantizer 14 quantizes a differential value output from the subtracter 12, and outputs an encoded code Y.sub.i to an output terminal 16 for transmission to a transmission channel.
The encoded code Y.sub.i is also supplied to an inverse quantizer 18. The inverse quantizer 18 converts the supplied encoded code Y.sub.i into a differential value (a representative quantized value). The predictive value (to be described later) is added to the representative quantized value in an adder 20, and a value corresponding to the input sampled value is output (this output is hereinafter termed a "restored value"). Since the restored value includes a quantized error, it has the possibility to exceed a range which the original input sampled value may have (this range is termed hereinafter briefly an "encoded range").
Accordingly, the amplitude of the restored value is limited within the encoded range of the original sampled value by a limiter 22, and the resultant value is supplied as a local decoded value X.sub.i to a D-type flip-flop 24 which is a predictive unit. In this example, since the decoded value of the preceding value is used as the predictive value, the predictive unit is a D-type flip-flop. The D-type flip-flop 24 supplies the subtracter 12 and the adder 20 with the local decoded value X.sub.i as the predictive value at the next clock cycle.
At this moment, the probability distribution of the differential value beween the predictive value and the input sampled value is generally skewed to portions having small absolute values. Hence, it is possible to compress the amount of information by making quantization steps fine in regions where differential values have small absolute values, and by making quantization steps coarse in regions where differential values have large absolute values.
In the example shown in FIG. 1, however, quantization steps are large in portions where predictive errors are large, such as an edge portion of an image, and hence quantization errors have very large values. Particularly at a level near a quantization boundary value (a threshold value between adjacent quantized codes) of a quantizer in a region where a predictive error is large, a representative quantized value changes with time even in a still-picture portion due to noise and the like. Accordingly, this small change in value results in a large change in value, which causes a large deterioration in picture quality. Such a deterioration in picture quality is particularly pronounced at an edge portion of an image where a predictive error is large, and is named "edge business" because the values of picture elements near an edge change with time.
Such a problem is not peculiar to the DPCM method, as described above, but is a problem which generally occurs in all coding systems having coarse quantization steps.